Parallel Computing Engineer

Department Icon IT / Software Development & Related
Posted: 10 months ago
3-8 years
Remote
IT / Software Development & Related
work from office
Full Time

Posted: 10 months ago
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Job Description

At Crossing Hurdles, we work as a referral partner. We refer candidates to our partner that collaborates with worlds leading AI research labs to build and train cutting-edge AI models.


Position: Parallel Computing Engineer

Type: Hourly Contract

Compensation: $10.5 per hour

Location: India (Remote)

Commitment: Part-time (20-30 hours/week), flexible


Role Responsibilities:

  • Accelerate numeric and simulation kernels using GPU/CPU parallelism.
  • Optimize workloads through memory-hierarchy tuning and communication reduction strategies.
  • Scale large computational workflows across distributed clusters using MPI, NCCL, and Slurm.
  • Profile, benchmark, and tune performance using tools like nvprof and nsys.
  • Build reproducible HPC pipelines using Python, NumPy, and SciPy.
  • Integrate parallel computing optimizations into production AI and scientific systems.
  • Collaborate with researchers and engineers to enhance performance across large-scale computational workloads.

Requirements:

  • Background in computer science, high-performance computing, or applied mathematics.
  • Hands-on experience with GPU/CPU parallel programming (CUDA, OpenMP).
  • Strong understanding of distributed execution frameworks (MPI, NCCL, Slurm).
  • Proficiency in Python with scientific computing libraries (NumPy, SciPy).
  • Experience profiling and optimizing workloads using tools like nvprof and nsys.
  • Strong understanding of memory hierarchy, communication overhead, and scalability constraints.
  • Interest in accelerating AI training, simulations, and scientific computations through HPC techniques.

Key Domains:

Applicants with strengths in the following domains are highly encouraged to apply:

  • High-Performance Computing (HPC): Parallel programming, cluster execution, GPU/CPU optimization
  • Distributed Systems: MPI, NCCL, Slurm, cluster scaling
  • Scientific Computing: Numeric kernels, simulations, Python-based HPC workflows
  • Performance Engineering: Profiling, benchmarking, memory tuning
  • AI Acceleration: HPC methods for AI training and large-scale models

Application Process:

  • Apply for the job role
  • Await the official message/email from our recruitment team (typically within 12 days)

Skills

CudaPythonOpenmpParallel ComputingComputationPythonDistributed Systems

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